Image Stitching Experiment for Two Images

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Resource Overview

This experiment focuses on stitching two images by first using RANSAC (Random Sample Consensus) to eliminate mismatched feature pairs and estimate the affine transformation matrix. One image is then transformed using the estimated affine parameters before performing the final stitching operation.

Detailed Documentation

In this experiment, we implement image stitching techniques to combine two images. The process begins by detecting and matching keypoint features (typically using algorithms like SIFT or ORB) between the images. We then apply the RANSAC method to robustly eliminate outlier matches and estimate a precise affine transformation matrix. The affine matrix estimation involves solving for rotation, translation, and scaling parameters using a minimum of three matched point pairs. Subsequently, we perform an affine transformation on one image using functions like cv2.warpAffine() in OpenCV to align it with the second image's perspective. Finally, we blend the transformed image with the target image using techniques such as linear blending or multi-band blending to create a seamless composite. This approach ensures accurate alignment while preserving critical visual information from both original images.

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